The cryo-EM resolution revolution has heralded a new era in our understanding of eukaryotic lipid flippases with a rapidly growing number of high-resolution structures. Flippases belong to the P4 family of ATPases (type IV P-type ATPases) that largely follow the reaction cycle proposed for the more extensively studied cation-transporting P-type ATPases. However, unlike the canonical P-type ATPases, no flippase cargos are transported in the phosphorylation half-reaction. Instead of being released into the intracellular or extracellular milieu, lipid cargos are transported to their destination at the inner leaflet of the membrane. Recent flippase structures have revealed multiple conformational states during the lipid transport cycle. Nonetheless, critical conformational states capturing the lipid cargo \"in transit\" are still missing. In this review, we highlight the amazing structural advances of these lipid transporters, discuss various perspectives on catalytic and regulatory mechanisms in the literature, and shed light on future directions in further deciphering the detailed molecular mechanisms of lipid flipping.

Cryo-electron microscopy (cryoEM) has become a well established technique to elucidate the 3D structures of biological macromolecules. Projection images from thousands of macromolecules that are assumed to be structurally identical are combined into a single 3D map representing the Coulomb potential of the macromolecule under study. This article discusses possible caveats along the image-processing path and how to avoid them to obtain a reliable 3D structure. Some of these problems are very well known in the community. These may be referred to as sample-related (such as specimen denaturation at interfaces or non-uniform projection geometry leading to underrepresented projection directions). The rest are related to the algorithms used. While some have been discussed in depth in the literature, such as the use of an incorrect initial volume, others have received much less attention. However, they are fundamental in any data-analysis approach. Chiefly among them, instabilities in estimating many of the key parameters that are required for a correct 3D reconstruction that occur all along the processing workflow are referred to, which may significantly affect the reliability of the whole process. In the field, the term overfitting has been coined to refer to some particular kinds of artifacts. It is argued that overfitting is a statistical bias in key parameter-estimation steps in the 3D reconstruction process, including intrinsic algorithmic bias. It is also shown that common tools (Fourier shell correlation) and strategies (gold standard) that are normally used to detect or prevent overfitting do not fully protect against it. Alternatively, it is proposed that detecting the bias that leads to overfitting is much easier when addressed at the level of parameter estimation, rather than detecting it once the particle images have been combined into a 3D map. Comparing the results from multiple algorithms (or at least, independent executions of the same algorithm) can detect parameter bias. These multiple executions could then be averaged to give a lower variance estimate of the underlying parameters.

The rapid spread of COVID-19 is motivating development of antivirals targeting conserved SARS-CoV-2 molecular machinery. The SARS-CoV-2 genome includes conserved RNA elements that offer potential small-molecule drug targets, but most of their 3D structures have not been experimentally characterized. Here, we provide a compilation of chemical mapping data from our and other labs, secondary structure models, and 3D model ensembles based on Rosetta\'s FARFAR2 algorithm for SARS-CoV-2 RNA regions including the individual stems SL1-8 in the extended 5\' UTR; the reverse complement of the 5\' UTR SL1-4; the frameshift stimulating element (FSE); and the extended pseudoknot, hypervariable region, and s2m of the 3\' UTR. For eleven of these elements (the stems in SL1-8, reverse complement of SL1-4, FSE, s2m and 3\' UTR pseudoknot), modeling convergence supports the accuracy of predicted low energy states; subsequent cryo-EM characterization of the FSE confirms modeling accuracy. To aid efforts to discover small molecule RNA binders guided by computational models, we provide a second set of similarly prepared models for RNA riboswitches that bind small molecules. Both datasets (\'FARFAR2-SARS-CoV-2\', https://github.com/DasLab/FARFAR2-SARS-CoV-2; and \'FARFAR2-Apo-Riboswitch\', at https://github.com/DasLab/FARFAR2-Apo-Riboswitch\') include up to 400 models for each RNA element, which may facilitate drug discovery approaches targeting dynamic ensembles of RNA molecules.

System xc - is an amino acid antiporter that imports L-cystine into cells and exports intracellular L-glutamate, at a 1:1 ratio. As L-cystine is an essential precursor for glutathione synthesis, system xc - supports tumor cell growth through glutathione-based oxidative stress resistance and is considered as a potential therapeutic target for cancer treatment. System xc - consists of two subunits, the light chain subunit SLC7A11 (xCT) and the heavy chain subunit SLC3A2 (also known as CD98hc or 4F2hc), which are linked by a conserved disulfide bridge. Although the recent structures of another SLC7 member, L-type amino acid transporter 1 (LAT1) in complex with CD98hc, have provided the structural basis toward understanding the amino acid transport mechanism, the detailed molecular mechanism of xCT remains unknown. To revealthe molecular mechanism, we performed single-particle analyses of the xCT-CD98hc complex. As wild-type xCT-CD98hc displayed poor stability and could not be purified to homogeneity, we applied a consensus mutagenesis approach to xCT. The consensus mutated construct exhibited increased stability as compared to the wild-type, and enabled the cryoelectron microscopy (cryo-EM) map to be obtained at 6.2 Å resolution by single-particle analysis. The cryo-EM map revealed sufficient electron density to assign secondary structures. In the xCT structure, the hash and arm domains are well resolved, whereas the bundle domain shows some flexibility. CD98hc is positioned next to the xCT transmembrane domain. This study provides the structural basis of xCT, and our consensus-based strategy could represent a good choice toward solving unstable protein structures.

Cryo-electron microscopy (cryoEM) is becoming popular as a tool to solve biomolecular structures with the recent availability of direct electron detectors allowing automated acquisition of high resolution data. The Bsoft software package, developed over 20 years for analyzing electron micrographs, offers a full workflow for validated single particle analysis with extensive functionality, enabling customization for specific cases. With the increasing use of cryoEM and its automation, proper validation of the results is a bigger concern. The three major validation approaches, independent data sets, resolution-limited processing, and coherence testing, can be incorporated into any Bsoft workflow. Here, the main workflow is divided into four phases: (i) micrograph preprocessing, (ii) particle picking, (iii) particle alignment and reconstruction, and (iv) interpretation. Each of these phases represents a conceptual unit that can be automated, followed by a check point to assess the results. The aim in the first three phases is to reconstruct one or more validated maps at the best resolution possible. Map interpretation then involves identification of components, segmentation, quantification, and modeling. The algorithms in Bsoft are well established, with future plans focused on ease of use, automation and institutionalizing validation.

Cryo-electron microscopy (cryo-EM) can provide low-resolution density maps of large macromolecular assemblies. As the number of structures deposited in the Protein Data Bank by fitting a high-resolution structure into a low-resolution cryo-EM map is increasing, there is a need to revise the protocols and improve the measures for fitting. A recent study suggested using a combination of multiple automated flexible fitting approaches to improve the interpretation of cryo-EM data. The current work further explores the use of multiple approaches by validating this \"consensus\" fitting approach and deriving a local reliability measure. Here four different flexible fitting approaches are applied for fitting an initial structure into a simulated density map of known target structure from a dataset of proteins. It is found that the models produced from different approaches often have a consensus in conformation and are also near to the target structure, whereas cases not showing consensus are away from the target. A high correlation is also observed between the RMSF profiles calculated with respect to the average and the target structures, which indicates that the relation between consensus and accuracy can also be extended to a per-residue level. Therefore, the RMSF among the fitted models is proposed as a local reliability measure, which can be used to assess the reliability of the fit at specific regions. Hence, we encourage the community to use consensus flexible fitting with different methods to report on local reliability of the resulting models and improve the interpretation of cryo-EM data.

Cryo-elecron microscopy (cryo-EM) can provide important structural information of large macromolecular assemblies in different conformational states. Recent years have seen an increase in structures deposited in the Protein Data Bank (PDB) by fitting a high-resolution structure into its low-resolution cryo-EM map. A commonly used protocol for accommodating the conformational changes between the X-ray structure and the cryo-EM map is rigid body fitting of individual domains. With the emergence of different flexible fitting approaches, there is a need to compare and revise these different protocols for the fitting. We have applied three diverse automated flexible fitting approaches on a protein dataset for which rigid domain fitting (RDF) models have been deposited in the PDB. In general, a consensus is observed in the conformations, which indicates a convergence from these theoretically different approaches to the most probable solution corresponding to the cryo-EM map. However, the result shows that the convergence might not be observed for proteins with complex conformational changes or with missing densities in cryo-EM map. In contrast, RDF structures deposited in the PDB can represent conformations that not only differ from the consensus obtained by flexible fitting but also from X-ray crystallography. Thus, this study emphasizes that a \"consensus\" achieved by the use of several automated flexible fitting approaches can provide a higher level of confidence in the modeled configurations. Following this protocol not only increases the confidence level of fitting, but also highlights protein regions with uncertain fitting. Hence, this protocol can lead to better interpretation of cryo-EM data.

The archetypical member of the small multidrug-resistance family is EmrE, a multidrug transporter that extrudes toxic polyaromatic cations from the cell coupled to the inward movement of protons down a concentration gradient. The architecture of EmrE was first defined from the analysis of two-dimensional crystals by cryoelectron microscopy (cryo-EM), which showed that EmrE was an unusual asymmetric dimer formed from a bundle of eight alpha-helices. The most favoured interpretation of the structure was that the monomers were oriented in opposite orientations in the membrane in an antiparallel orientation. A model was subsequently built based upon the cryo-EM data and evolutionary constraints and this model was consistent with mutagenic data indicating which amino-acid residues were important for substrate binding and transport. Two X-ray structures that differed significantly from the cryo-EM structure were subsequently retracted owing to a data-analysis error. However, the revised X-ray structure with substrate bound is extremely similar to the model built from the cryo-EM structure (r.m.s.d. of 1.4 A), suggesting that the proposed antiparallel orientation of the monomers is indeed correct; this represents a new structural paradigm in membrane-protein structures. The vast majority of mutagenic and biochemical data corroborate this structure, although cross-linking studies and recent EPR data apparently support a model of EmrE that contains parallel dimers.